technical introduction to ariana rescue robot team

AriAnA Rescue Robot Team

Amir H. SoltanzadehRobotics Lab @ Engineering School

IAUCTB

Technical Introduction

IAUCTB 2/40Robotics Lab @ Engineering School

Outlines

Introduction to USAR Robotics• USAR as a real-world problem• RoboCup Rescue Robot League

Technical introduction• Mechanical overview• Hardware architecture• Software architecture


USAR Robotics


What is USAR Robotics?

USAR: Urban Search And Rescue

SearchTo look through in a place or in an area carefully in order to find something missing or lost

RescueTo free or deliver victim from confinement.


What is USAR Robotics?

Developing robots to be used in USAR application

SearchTo look through in a place or in an area carefully in order to find something missing or lost

RescueTo free or deliver victim from confinement.


Why use robots for USAR?

3-D law

Robots can help in Dirty, Dangerous, Dull Tasks.

They can do what rescuers or rescue dogs can’t!• voids smaller than person can enter• voids on fire or oxygen depleted

» Lose ½ cognitive attention with each level of protection

Void on fire

Void:1’x2.5’x60’



3-D law


The most important person in a rescue attempt is the rescuer!• Not enough trained people

» 1 survivor, entombed: 10 rescuers, 4 hours» 1 survivor, trapped/crushed: 10 rescuers, 10 hours

135 rescuers died Mexico City, 65 in confined spaces



3-D law


They save time!• Time is very critical

30 Min 1 Day 2 Days 3 Days 4 Days 5 Days0.0

10.0

20.0

30.0

40.0

50.0

60.0

19.4

42.2

5.61.1 0.7 0.3

1.9

9.9

9.72.2 3.0 4.0

Survival Rate

Dead

Survived

Time

% R

escu

ed

Golden 24 hours


Taxonomy of USAR Robots

USAR robots

MAVUG

V

Man-packable

Man-portable

Big-size

USV

UAV


Brief History of USAR Robotics

Oklahoma City bombing (1995)

The Idea of using robots in USAR domain (by R. Murphy and J. Blitch)

Hanshi-Awaji earthquake in Kobe City (1995)

The trigger for the RoboCup Rescue initiative

WTC 9/11 (2001) First practical usage of robots in real USAR application

After 2001 rescue robots were applied in several occasions:• Boat robots (USV) were used after hurricanes Charley, Dennis,

Katrina and Wilma • Aerial robots (UAV) were used after earthquake in L’Aquila, Italy

0

61 5


RoboCup Rescue Robot League

RoboCupRoboCup

JuniorsJuniors SeniorsSeniors

SoccerSoccer RescueRescue @Home@HomeSoccerSoccer

RescueRescue

DanceDance

SimulationSimulation

Small SizeSmall Size

Middle SizeMiddle Size

Standard PlatformStandard Platform

HumanoidHumanoid

SimulationSimulation

RobotRobot



Tasks• Finding victims in a simulated destructed building• Identifying detected victims (signs of life and identity)• Marking victims’ locations on an automatically generated

map



Test Arena Yellow

• Ramps• Autonomous Robots

Only Orange

• Steep Ramp• Stairs

Red• Step-Field

Radio Drop-Out• Autonomous Mobility


AriAnA Rescue Robot Team


Brief History

Start (2005) • Research phase in Shahed Research Center (2005) Becoming official team of IAUCTB (2006) • 7th place in final ranking of RoboCup Rescue (2006) Joining with AVA – Malaysia (2008) • 2nd place in ISME 2008 student projects (2008) • 7th place in RoboCup Rescue (2009) • 1st place in Khwarizmi Robotics Competitions (2010)

2006 2007 2009 2010 2008 2009

AVA - Malaysia (ISOP Int. Co.)


Mechanical Overview

Mobile manipulation in rough terrain: Locomotion Manipulation


Locomotion

Mobility as a problem: Rescue robots should be highly mobile. Compromising between Mobility and Complexity of

locomotion systems is inevitable.• Biomimicry has not yet been a suitable solution due to

technical limitations:» Nature does not create efficient locomotion systems (living

beings must do numerous things).» Intelligent control of advanced mobility robots is

computationally power hungry.

Complexity

Mobility

as less complicated as possible to fulfill a task

Various Platforms)for variety of terrains(

EfficiencyComplexity


Hybrid Locomotion

Our solution:

Legged

Designing a walking mechanism which is not necessarily inspired from the nature.

Legged systems are very hard to control!

Higher maneuverabilityon rough terrains

Triangular Tracked Wheel

Decreasing complexity of control system by means of semi-active joint controlling

WheeledTracked

Higher efficiencywhile steering

Higher traction +Lower ground pressure


Concept of TTW Mechanism

2 DOF: Tracks (velocity & torque controlled) Triangular frames (semi-active joint):

• Active (position, velocity & torque controlled)• Passive



Active joint controlling:• Continuous movement: Tracks traveling → suitable for flat grounds

(This type is also available in passive mode)• Discrete movement: Triangular frames rotation → for rough terrains• Combined movement: Both tracks and triangles → for ultra-rough terrains



Passive joint controlling: • Surface adaptation:

» Lateral adaptation: Increasing traction without control process» Axial adaptation: Passing obstacles without control process

Not actually controlled but is monitored!


Manipulator

Manipulator:• Surveillance

» Camera » Victim detection sensors

• Manipulation» Camera» Victim detection sensors» Gripper

Problems:• DOF:

» Maneuverability» Complexity

• Accuracy• Payload End effector’s orientation correction mechanism:

Combination of two parallelogram four-bar linkage with flexible links


Hardware Architecture

Power Management System Main Board Communication System Motors & Drivers Video System Sensors


Power Management System

Web based PMS:• Power distribution• Monitoring (voltage & current) • Web Interfaced• Intelligent control• Self-health check


Main Board

Industry grade Motherboard• Small (115 x 165 mm) • Powerful

» Pentium M 1.4 GHz, 2M L2 cache• Robust

» Fanless (-40 to +80 C)» Compact Flash compatible» PC/104-plus compatible» 0% ~ 90% relative humidity


Communications

Internal• Wired

External • Wireless Communication

» 5 GHz IEEE802.11a Access Point / Bridge


Motors & Drivers

High efficiency brushless DC motors • ~ 90% efficient• 120 – 200W nominal power

Highly efficient Gearhead• ~ 80% efficient

Incremental Encoder• 1500 cpr

Driver• Torque control• Velocity control• Position control


Video System

Camera• Miniature cam (QTY = 3)• Zoom cam (QTY = 1)

» Optical zoom» Auto/Manual control

Video Server• Industry grade VS

» Higher quality › Resolution: 720 x 480› Frame rate: up to 30 fps

» Robustness› 3g shock & 1g vibration


Sensors

Navigation• Dead reckoning

» Odometry» IMU

• Range sensors» Scanning Laser Range Finder

• Vision » Monocular» Stereo

• Proximity sensors» Ultrasonic

• GPS (Outdoor only)


Sensors

Victim identification • Temperature

» Thermal imaging camera» Temperature scanner

• Vision » Monocular

• Breathing» CO2 sensor


Software Architecture

Robotic Server HRI SLAM


Robotic Server

Player (started in 2000)• A universal driver for robotics

Stage• 2D multi-robot simulator

Gazebo (started in 2003)• High-fidelity 3D multi-robot simulator


Player / Stage / Gazebo

Player)server(

Controller)client(

Controller)client(

Controller)client(

Controller)client(

Player)server(

TCP, UDP,Jini, Ice

RS232, USB, 1394, TCP, Shared Mem

Stage (2D simulation)Gazebo (3D simulation)

©Brian Gerkey


Human Robot Interaction

Easy to understand Graphical User Interface (GUI)• Video-centric GUI

Popular X-Box controller


SLAM

SLAM: Simultaneous Localization And Mapping• Generating a map of unknown environment while

localizing the mapping system within that map


Navigation and SLAM

Mapping

Motion control

Localization

SLAM

Active localizationExploration

Integrated approaches

©Makarenko et al


The SLAM Problem

Ground truth map(what happens)

Local map(what robot sees)

Global map(what robot thinks)

Given • Robot controls• Nearby measurements

Estimate• Robot state (position, orientation)• Map of world features


Structure of SLAM Problem

uk

Xk-1

mi

mj

Xk

Zk-1,i

Zk,j


Why SLAM is hard?

Chicken and egg problem: robot path and map are both unknown

In the real world, the mapping between observations and landmarks is unknown

Picking wrong data associations can have catastrophic consequences

Pose error correlates data associations

Robot poseuncertainty


Questions

Thank You!

technical introduction to ariana rescue robot team

Technology

rescue robots

use robots

rescue attempt

rescue dogs

usar roboticsusar

usar domain

real usar applicationafter

practical usage of robots